New predictive model for monitoring bone remodeling
Bibliographic record
Abstract
The aim of this article was to present a new thermodynamic-based model for bone remodeling which is able to predict the functional adaptation of bone in response to changes in both mechanical and biochemical environments. The model was based on chemical kinetics and irreversible thermodynamic principles, in which bone is considered as a self-organizing system that exchanges matter, energy and entropy with its surroundings. The governing equations of the mathematical model have been numerically solved using Matlab software and implemented in ANSYS software using the Finite Element Method. With the aid of this model, the whole inner structure of bone was elucidated. The current model suggested that bone remodeling was a dynamic process which was driven by mechanical loading, metabolic factors and other external contributions. The model clearly indicated that in the absence of mechanical stimulus, the bone was not completely resorbed and reaches a new steady state after about 50% of bone loss. This finding agreed with previous clinical studies. Furthermore, results of virtual computations of bone density in a composite femur showed the development of a dense cortical bone around the medullary canal and a dense trabeculae bone between the femoral head and the calcar region of the medial cortex due to compressive stresses. The comparison of the predicted bone density with the structure of the proximal femur obtained from X-rays and using strain energy density gave credibility to the current model.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".